We’re going to make some plotly plots.
library(tidyverse)
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library(p8105.datasets)
library(plotly)
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## layout
data("nyc_airbnb")
nyc_airbnb =
nyc_airbnb %>%
mutate(rating = review_scores_location / 2) %>%
select(
borough = neighbourhood_group, neighbourhood, price, room_type, lat, long, rating) %>%
filter(
borough == "Manhattan",
room_type == "Entire home/apt",
price %in% 100:500
) %>%
drop_na(rating)
Let’s make a scatterplot!!
nyc_airbnb %>%
mutate(
text_label = str_c("Price: ", price, "\nRating: ", rating) #combine string "Price" and price var
) %>%
plot_ly(
x = ~lat, y = ~long, color = ~price,
type = "scatter", mode = "markers",
alpha = 0.5, text = ~text_label
)
Can we make boxplots??
nyc_airbnb %>%
mutate(neighbourhood = fct_reorder(neighbourhood, price)) %>%
plot_ly(
y = ~price, color = ~neighbourhood,
type = "box", colors = "viridis")
Can we make a bar plot?
nyc_airbnb %>%
count(neighbourhood) %>%
mutate(neighbourhood = fct_reorder(neighbourhood, n)) %>%
plot_ly(
x = ~neighbourhood, y = ~n,
type = "bar")
ggp_scatterplot =
nyc_airbnb %>%
ggplot(aes(x = lat, y = long, color = price)) +
geom_point()
ggplotly(ggp_scatterplot)
easy to create, but slow interaction
Not here though.